Databricks Data Engineer

++Senior MDM / Databricks Data Engineer++Experience: 6--10+ Years

Key Skills: MDM, Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Data Quality, Data Governance

Role Summary

We are looking for an experienced MDM / Databricks Data Engineer to build scalable master data and integration solutions on a modern Databricks Lakehouse. The role will focus on common IDs, Golden Records, entity resolution, data quality, governance, and cross-platform data integration.

Key Responsibilities

· Design and implement MDM solutions, including common IDs, Golden Records, entity matching, deduplication, and survivorship rules.

• Integrate data from multiple source systems into the Databricks Lakehouse.

• Develop and optimize data pipelines using Databricks, PySpark, SQL, and Delta Lake.

• Build and enhance Bronze, Silver, and Gold data layers.

• Implement data quality, standardization, reconciliation, and validation processes.

• Support Unity Catalog, data lineage, access controls, cataloguing, and data governance.

• Implement data masking and anonymization for sensitive data.

• Build trusted, reusable data layers for cross-platform analytics and intelligence.

• Collaborate with business, architecture, and engineering teams to define MDM and data integration requirements.

Required Skills

· Strong experience in Master Data Management (MDM) and data engineering.

• Hands-on expertise in Databricks, PySpark, SQL, Delta Lake, and Lakehouse architecture.

• Experience with Golden Records, common IDs, entity resolution, deduplication, and data quality.

• Good understanding of Unity Catalog, data governance, metadata, and lineage.

• Experience integrating data from multiple enterprise platforms.

• Knowledge of Medallion Architecture and data privacy/anonymization.

Good to Have

· Experience with Informatica MDM/IDMC, Reltio, Profisee, Semarchy, or similar MDM platforms.

• Cloud experience with Azure, AWS, or GCP.

• Exposure to large-scale data modernization or migration programs.